Determining arterial pulse wave transit time from vpg and ecg/ekg signals

Abstract

What is disclosed is a system and method for determining arterial pulse wave transit time for a subject. In one embodiment, a video is received comprising a plurality of time-sequential image frames of a region of exposed skin of a subject where a videoplethysmographic (VPG) signal can be registered by at least one imaging channel of the video device used to capture that video. Also received is an electrocardiogram (ECG) signal obtained using at least one sensor placed on the subject's body where a ECG signal can be obtained. Batches of image frames are processed to obtain a continuous VPG signal for the subject. Temporally overlapping VPG and ECG signals are analyzed to obtain a pulse wave transit time between a reference point on the VPG signal and a reference point on the ECG signal. The pulse transit time is used to assess pathologic conditions such as peripheral vascular disease.

What is claimed is:  
     
         1 . A method for determining pulse wave transit time for a subject, comprising:
 receiving a video acquired by a video imaging device, said video comprising a plurality of time-sequential image frames of a region of exposed skin of a subject where a videoplethysmographic (VPG) signal can be registered by at least one imaging channel of said video imaging device;   receiving an electrocardiogram (ECG) signal obtained using at least one sensor placed on said subject's body where an ECG signal can be obtained;   extracting a continuous VPG signal from batches of said image frames; and   processing temporally overlapping VPG and ECG signals to obtain a pulse transit time between a reference point on said VPG signal and a reference point on said ECG signal.   
     
     
         2 . The method of  claim 1 , wherein said video imaging device is any of: a monochrome video camera, a color video camera, an infrared video camera, a multispectral video imaging device, a hyperspectral video imaging device, and a hybrid video imaging device comprising any combination hereof. 
     
     
         3 . The method of  claim 1 , wherein, in advance of processing said image frames, further comprising compensating for any of: a motion induced blur, an imaging blur, and slow illuminant variation. 
     
     
         4 . The method of  claim 1 , wherein processing said image frames to obtain said VPG signal comprises:
 isolating pixels in said image frames associated with said region of exposed skin;   processing said isolated pixels to obtain a time-series signal; and   extracting, from said time-series signal, a VPG signal for said subject.   
     
     
         5 . The method of  claim 4 , wherein pixels are isolated in said image frames using any of: pixel classification, object identification, thoracic region recognition, color, texture, spatial features, spectral information, pattern recognition, face detection, facial recognition, and a user input. 
     
     
         6 . The method of  claim 1 , wherein, in advance of extracting said VPG signal from said time-series signal, further comprising any of:
 detrending said time-series signal to remove non-stationary components;   filtering said time-series signal with a cutoff frequency defined as a function of a frequency of said subject's cardiac pulse; and   performing automatic peak detection on said filtered signal.   
     
     
         7 . The method of  claim 1 , wherein, in advance of processing said VPG and ECG signals to obtain said pulse wave transit time, further comprising temporally synchronizing said VPG and ECG signal acquisition. 
     
     
         8 . The method of  claim 1 , wherein said reference point on said ECG signal is a peak point of a R wave and said reference point on said VPG signal is a characteristic point on said VPG signal comprising any of: a maximum, a minimum, an average point between a maximum and a minimum, a maximum of a VPG signal derivative, and a maximum of a second derivative. 
     
     
         9 . The method of  claim 1 , wherein both said video imaging device and said ECG sensor are integrated into any of: a smartphone, an iPad, a tablet-PC, a laptop, and a computer workstation. 
     
     
         10 . The method of  claim 1 , further comprising determining whether a movement occurred during acquisition of said video image frames. 
     
     
         11 . The method of  claim 1 , further comprising determining, from said pulse transit time, any of: blood pressure, blood vessel dilation over time, blood vessel blockage, and blood flow velocity. 
     
     
         12 . The method of  claim 11 , further comprising determining an occurrence of any of: cardiac arrhythmia, cardiac stress, heart disease, and peripheral vascular disease. 
     
     
         13 . The method of  claim 1 , further comprising communicating said pulse transit time to any of: a storage device, a display device, and a remote device over a network. 
     
     
         14 . A system for determining arterial pulse wave transit time for a subject, the system comprising:
 a processor in communication with a memory and storage device, said processor executing machine readable instructions for performing:
 receiving a video acquired by a video imaging device, said video comprising a plurality of time-sequential image frames of a region of exposed skin of a subject where a videoplethysmographic (VPG) signal can be registered by at least one imaging channel of said video imaging device; 
 receiving an electrocardiogram (ECG) signal obtained using at least one sensor placed on said subject's body where an ECG signal can be obtained; 
 extracting a continuous VPG signal from batches of said image frames; and 
 processing temporally overlapping VPG and ECG signals to obtain a pulse transit time between a reference point on said VPG signal and a reference point on said ECG signal. 
   
     
     
         15 . The system of  claim 14 , wherein said video imaging device is any of: a monochrome video camera, a color video camera, an infrared video camera, a multispectral video imaging device, a hyperspectral video imaging device, and a hybrid video imaging device comprising any combination hereof. 
     
     
         16 . The system of  claim 14 , wherein, in advance of processing said image frames, further comprising compensating for any of: a motion induced blur, an imaging blur, and slow illuminant variation. 
     
     
         17 . The system of  claim 14 , wherein processing said image frames to obtain said VPG signal comprises:
 isolating pixels in said image frames associated with said region of exposed skin;   processing said isolated pixels to obtain a time-series signal; and   extracting, from said time-series signal, a VPG signal for said subject.   
     
     
         18 . The system of  claim 17 , wherein pixels are isolated in said image frames using any of: pixel classification, object identification, thoracic region recognition, color, texture, spatial features, spectral information, pattern recognition, face detection, facial recognition, and a user input. 
     
     
         19 . The system of  claim 14 , wherein, in advance of extracting said VPG signal from said time-series signal, further comprising any of:
 detrending said time-series signal to remove non-stationary components;   filtering said time-series signal with a cutoff frequency defined as a function of a frequency of said subject's cardiac pulse; and   performing automatic peak detection on said filtered signal.   
     
     
         20 . The system of  claim 14 , wherein, in advance of processing said VPG and ECG signals to obtain said pulse wave transit time, further comprising temporally synchronizing said VPG and ECG signal acquisition. 
     
     
         21 . The system of  claim 14 , wherein said reference point on said ECG signal is a peak point of a R wave and said reference point on said VPG signal is a characteristic point on said VPG signal comprising any of: a maximum, a minimum, an average point between a maximum and a minimum, a maximum of a VPG signal derivative, and a maximum of a second derivative. 
     
     
         22 . The system of  claim 14 , wherein both said video imaging device and said ECG sensor are integrated into any of: a smartphone, an iPad, a tablet-PC, a laptop, and a computer workstation. 
     
     
         23 . The system of  claim 14 , further comprising determining, from said pulse transit time, any of: blood pressure, blood vessel dilation over time, blood vessel blockage, and blood flow velocity. 
     
     
         24 . The system of  claim 23 , further comprising determining an occurrence of any of: cardiac arrhythmia, cardiac stress, heart disease, and peripheral vascular disease. 
     
     
         25 . The system of  claim 14 , further comprising communicating said pulse transit time to any of: a storage device, a display device, and a remote device over a network.